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Remote Audio Machine Learning Jobs in Darien, CT

Data Engineer

New York, NY · Remote

$140K - $180K/yr

Bonus: experience orchestrating machine learning workflows (training pipelines, model retraining ... Remote Fridays * Happy Hours and other local events Compensation Range: $140K - $180K

Data Engineer

New York, NY · Remote

$140K - $180K/yr

Bonus: experience orchestrating machine learning workflows (training pipelines, model retraining ... Remote Fridays * Happy Hours and other local events Compensation Range: $140K - $180K

Data Engineer

New York, NY · On-site +1

$140K - $180K/yr

Bonus: experience orchestrating machine learning workflows (training pipelines, model retraining ... Remote Fridays * Happy Hours and other local events

We have a flexible work environment and allow remote work depending on one's personal choice. Responsibilities: As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the ...

AI Data Engineer

New York, NY · On-site +1

$125K - $150K/yr

Collaborate with data scientists and machine learning engineers to understand data requirements for ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

AI Data Engineer

New York, NY · Remote

$117K - $140K/yr

Collaborate with data scientists and machine learning engineers to understand data requirements for ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

Remote Role Responsibilities * Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks. * Review model-generated implementations involving model ...

Remote Role Responsibilities * Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks. * Review model-generated implementations involving model ...

Showing results 21-40

Remote Audio Machine Learning information

See Darien, CT salary details

$30.8K

$88.1K

$178.9K

How much do remote audio machine learning jobs pay per year?

As of Aug 13, 2026, the average yearly pay for remote audio machine learning in Darien, CT is $88,089.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,200.00 and $117,900.00 per year, depending on experience, location, and employer.

What is the difference between Remote Audio Machine Learning vs Remote Audio Engineer?

AspectRemote Audio Machine LearningRemote Audio Engineer
Required CredentialsBackground in machine learning, data science, or AI; often a degree in computer science or related fieldsAudio engineering, sound design, or music production degree or certification
Work EnvironmentPrimarily focused on developing algorithms, data analysis, and model training, often in a tech or research settingRecording, mixing, editing audio, often in studios or remote production setups
Employer & Industry UsageTech companies, research labs, AI startups working on audio recognition or enhancementMusic, film, broadcasting, and media production companies

Remote Audio Machine Learning specialists focus on developing algorithms to process and analyze audio data, while Remote Audio Engineers handle the practical aspects of recording and editing sound. Both roles may collaborate but serve different functions within the audio industry.

How does a remote audio machine learning role typically collaborate with cross-functional teams, and what communication tools are commonly used?

In a Remote Audio Machine Learning position, collaboration with cross-functional teams such as software engineers, data scientists, and product managers is essential. Regular communication is maintained through tools like Slack, Zoom, and project management platforms such as Jira or Trello. Team members often participate in virtual stand-ups, sprint planning sessions, and code reviews to ensure alignment on project goals and timelines. Effective asynchronous communication and clear documentation are especially important in remote settings to keep everyone informed and foster a productive workflow.

What are the key skills and qualifications needed to thrive as a remote audio machine learning engineer?

To thrive as a Remote Audio Machine Learning Engineer, you need strong foundations in digital signal processing, machine learning algorithms, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, and audio processing libraries (e.g., LibROSA), as well as experience with cloud platforms, is highly valuable. Excellent problem-solving skills, self-motivation, and clear remote communication are essential soft skills for collaborating across distributed teams. These competencies enable the development of robust, innovative audio ML solutions while ensuring effective teamwork and project delivery in a remote setting.

What is a remote audio machine learning?

A Remote Audio Machine Learning job involves using machine learning techniques to analyze, process, or generate audio data while working from a remote location. Professionals in this field develop algorithms for tasks such as speech recognition, music classification, noise reduction, or audio synthesis. They often work with large datasets, build and train models, and collaborate with teams online. These roles typically require skills in programming, signal processing, and experience with machine learning frameworks.

Senior Machine Learning Platform Engineer

Charlie Health

New York, NY • On-site, Remote

$114K - $157K/yr

Full-time

Re-posted 26 days ago


Charlie Health rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz


Job description

Why Charlie Health?

Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported.

Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection—between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home.

As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you.

About the Role

Charlie Health leads the nation in high-acuity virtual behavioral care, having delivered life-saving treatment to more than 100,000 clients nationwide. Our ML and AI capabilities are expanding rapidly—powering recommendation systems, clinical decision support, agentic AI products, and developer tooling—and the infrastructure underneath needs to scale with them.

As our first dedicated ML Platform Engineer, you'll define the technical direction and build the foundational systems that our data scientists, ML engineers, and product teams depend on to ship AI-powered features reliably and at scale. We have several models in production today and are investing in hosted GPU inference to support the next generation of our AI capabilities. You'll inherit and evolve existing infrastructure while building new platform capabilities—from multi-tenant model serving and GPU inference pipelines to multimodal data management, evaluation frameworks, observability, and infrastructure as code. You'll own the platform layer that makes ML/AI development at Charlie Health fast, safe, and repeatable as the team grows. If you care about building the systems that let others build great things, this team is for you.

Responsibilities

Infrastructure & Serving

  • Define technical direction for ML/AI infrastructure and make build-vs-buy decisions as the founding platform engineer
  • Design and operate multi-vendor AI infrastructure supporting client-facing and clinician-facing LLM applications across multiple LLM providers
  • Design, build, and operate production model serving systems; maintain infrastructure as code for reproducible ML environments, training pipelines, and deployment workflows
  • Develop high-performance GPU inference pipelines with low latency and high availability
  • Own the multimodal data pipeline layer—manage ingestion, processing, and serving of text, audio, and structured clinical data for ML and AI systems

AI Systems & Tooling

  • Create reliable infrastructure for agentic AI systems, including orchestration, monitoring, evaluation, and observability tooling
  • Build developer tooling that accelerates data science and ML engineering workflows across the organization

Observability & Operations

  • Own AI observability—build monitoring, alerting, and debugging capabilities for production ML systems
  • Partner with ML engineers, data scientists, and product teams to understand infrastructure needs and translate them into scalable platform capabilities
  • Foster a culture of collaboration and learning across engineering, product, and design through mentoring, documentation, presentations, and knowledge sharing
  • Participate in our on-call rotation to ensure model serving uptime, pipeline reliability, and infrastructure health
Requirements
  • 4+ years of professional experience in software engineering, with at least 2 years focused on ML infrastructure, ML platform, or AI systems engineering
  • Strong software engineering fundamentals in Python and deep infrastructure expertise
  • Familiarity with cloud ML services (AWS SageMaker, GCP Vertex AI, or similar) and CI/CD for ML pipelines
  • Experience with infrastructure as code (Terraform, Pulumi, or similar) and container orchestration (Kubernetes, ECS)
  • Experience building evaluation and observability systems for LLM-based or agentic AI applications is a plus
  • Excellent at managing ambiguity—able to break down big, messy problems into smaller parts with tractable solutions and clear iterations
  • Growth mindset and sense of humor; you welcome feedback, adapt quickly in a fast-paced environment, and foster a culture of learning and fun
  • Experience with a systems language (Go, Rust, or C++) is a plus

This role requires 4 days per week in our NYC office (Flatiron District). The team is entirely based out of NYC.

Benefits

Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here.

The total target base compensation for this role will be between $170,000-$220,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits.

Our Values
  • Connection: Care deeply & inspire hope.
  • Congruence: Stay curious & heed the evidence.
  • Commitment: Act with urgency & don't give up.

Please do not call our public clinical admissions line in regard to this or any other job posting.

Please be cautious of potential recruitment fraud. If you are interested in exploring opportunities at Charlie Health, please go directly to our Careers Page: https://www.charliehealth.com/careers/current-openings. Charlie Health will never ask you to pay a fee or download software as part of the interview process with our company. In addition, Charlie Health will not ask for your personal banking information until you have signed an offer of employment and completed onboarding paperwork that is provided by our People Operations team. All communications with Charlie Health Talent and People Operations professionals will only be sent from @charliehealth.com email addresses. Legitimate emails will never originate from gmail.com, yahoo.com, or other commercial email services.

Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals.

At Charlie Health, we value being an Equal Opportunity Employer. We strive to cultivate an environment where individuals can be their authentic selves. Being an Equal Opportunity Employer means every member of our team feels as though they are supported and belong. We value diverse perspectives to help us provide essential mental health and substance use disorder treatments to all young people.

Charlie Health applicants are assessed solely on their qualifications for the role, without regard to disability or need for accommodation.

By clicking "Submit application" below, you agree to Charlie Health's Privacy Policy and Terms of Service.

By submitting your application, you agree to receive SMS messages from Charlie Health regarding your application. Message and data rates may apply. Message frequency varies. You can reply STOP to opt out at any time. For help, reply HELP.


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